FAQ
4 May 2025 2025-12-27 14:56FAQ
Class Readiness
Computer Configuration
- Processor:
x64-based processor, x64 based architecture (Intel Core-i3/i5/i7)
Please Note: ARM Architecture Based Processor (like Snapdragon X Elite) not support Microsoft SQL Server. - Operating System:
64-bit operating system, Windows 10 Pro, Windows 11 Pro (Recommended) - RAM: 4 GB, 8 GB (Recommended)
- Hard Drive: SSD, NVMe (Recommended)
WhatsApp account
Download/Install Necessary Software
SQL Server 2025 Developer Edition & SQL Server Management Studio (SSMS)
Get the full-featured free edition, licensed for use as a development and test database in a non-production environment.
Power BI Desktop
Create rich, interactive reports with visual analytics at your fingertips—for free.
Visual Studio 2026 Community Edition
A fully-featured, extensible, free IDE for creating modern applications for Android, iOS, Windows, as well as web applications and cloud services.
Anaconda Navigator for Data Science
Launch data science applications from your desktop with Anaconda Navigator, Terminal Window Not Required.
Download Necessary Dataset
SQL/TSQL Tools
HR Dataset Emp
World Population
Explore the World Population Through Data
Discover population, economy, health, and more with the most comprehensive global statistics at your fingertips.
HR Database Dept
Brazilian E-Commerce
HR Database 05
Oscar Dataset
Sakila Database
Northwind Database
Download Necessary Dataset
Power BI Tools
Sales Data (.csv)
Use this dataset aims to analyze sales data over multiple years to identify key trends, customer behavior, product performance, and regional sales distribution. By leveraging structured business data, we can generate insights that support decision-making, improve operational efficiency, and enhance overall business strategy.
Sales KPI
A sales KPI dashboard is a visual tool that consolidates key performance indicators (KPIs) into interactive charts and graphs to provide a real-time, at-a-glance view of sales team performance against goals.
Sales Data (.xls)
Use this dataset aims to analyze sales data over multiple years to identify key trends, customer behavior, product performance, and regional sales distribution. By leveraging structured business data, we can generate insights that support decision-making, improve operational efficiency, and enhance overall business strategy.
London & Boston Data (.txt)
A sales KPI dashboard is a visual tool that consolidates key performance indicators (KPIs) into interactive charts and graphs to provide a real-time, at-a-glance view of sales team performance against goals.
Forecast Dataset
A forecast dataset contains historical and present information used to predict future outcomes, and examples include sales data for forecasting revenue, weather observation data for predicting weather patterns, and retail inventory data for anticipating demand.
Forecast Dataset
A forecast dataset contains historical and present information used to predict future outcomes, and examples include sales data for forecasting revenue, weather observation data for predicting weather patterns, and retail inventory data for anticipating demand.
Download Necessary Dataset
Python for Machine Learning
House Price
A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to main road, etc. The dataset is small yet, it’s complexity arises due to the fact that it has strong multicollinearity.
Clean Table
Clean Table Dataset
House Price
A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to main road, etc. The dataset is small yet, it’s complexity arises due to the fact that it has strong multicollinearity.
House Price
A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to main road, etc. The dataset is small yet, it’s complexity arises due to the fact that it has strong multicollinearity.
House Price
A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to main road, etc. The dataset is small yet, it’s complexity arises due to the fact that it has strong multicollinearity.
House Price
A simple yet challenging project, to predict the housing price based on certain factors like house area, bedrooms, furnished, nearness to main road, etc. The dataset is small yet, it’s complexity arises due to the fact that it has strong multicollinearity.
Download Necessary Dataset
Advanced Excel
Master Database
All research projects collect and use multiple datasets for a given unit of observation. Reference (Master) data sets are the second component of using a data map to organize data work in a research team. They allow the research team to keep track of individual units for each level of observation. For example, master data sets are useful for keeping track of each household if the unit of observation is individual households, each company if the unit of observation is individual companies, and so on. While master data sets take some time and effort to set up, they significantly reduce sources of error, and simplify the process of working with datasets from multiple sources – baseline data, endline data, administrative and monitoring data, etc.
Master Database
All research projects collect and use multiple datasets for a given unit of observation. Reference (Master) data sets are the second component of using a data map to organize data work in a research team. They allow the research team to keep track of individual units for each level of observation. For example, master data sets are useful for keeping track of each household if the unit of observation is individual households, each company if the unit of observation is individual companies, and so on. While master data sets take some time and effort to set up, they significantly reduce sources of error, and simplify the process of working with datasets from multiple sources – baseline data, endline data, administrative and monitoring data, etc.
Master Database
All research projects collect and use multiple datasets for a given unit of observation. Reference (Master) data sets are the second component of using a data map to organize data work in a research team. They allow the research team to keep track of individual units for each level of observation. For example, master data sets are useful for keeping track of each household if the unit of observation is individual households, each company if the unit of observation is individual companies, and so on. While master data sets take some time and effort to set up, they significantly reduce sources of error, and simplify the process of working with datasets from multiple sources – baseline data, endline data, administrative and monitoring data, etc.
Master Database
All research projects collect and use multiple datasets for a given unit of observation. Reference (Master) data sets are the second component of using a data map to organize data work in a research team. They allow the research team to keep track of individual units for each level of observation. For example, master data sets are useful for keeping track of each household if the unit of observation is individual households, each company if the unit of observation is individual companies, and so on. While master data sets take some time and effort to set up, they significantly reduce sources of error, and simplify the process of working with datasets from multiple sources – baseline data, endline data, administrative and monitoring data, etc.
Master Database
All research projects collect and use multiple datasets for a given unit of observation. Reference (Master) data sets are the second component of using a data map to organize data work in a research team. They allow the research team to keep track of individual units for each level of observation. For example, master data sets are useful for keeping track of each household if the unit of observation is individual households, each company if the unit of observation is individual companies, and so on. While master data sets take some time and effort to set up, they significantly reduce sources of error, and simplify the process of working with datasets from multiple sources – baseline data, endline data, administrative and monitoring data, etc.
Master Database
All research projects collect and use multiple datasets for a given unit of observation. Reference (Master) data sets are the second component of using a data map to organize data work in a research team. They allow the research team to keep track of individual units for each level of observation. For example, master data sets are useful for keeping track of each household if the unit of observation is individual households, each company if the unit of observation is individual companies, and so on. While master data sets take some time and effort to set up, they significantly reduce sources of error, and simplify the process of working with datasets from multiple sources – baseline data, endline data, administrative and monitoring data, etc.
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